AI Platform Engineer | 100% Remote

Hi,

Position: AI Platform Engineer

Location: 100% Remote

Duration: 12 + Months

Interview Mode: Video

Must Have:

* Current Health Insurance Customer Experience

Candidates from Approved States ONLY: DC, MD, VA

Eligibility: USC-EAD

JD

Key Responsibilities

(1)Platform Engineering & Cloud Configuration
-- Convert approved AI reference architectures into deployable cloud configurations across Azure, MuleSoft, and Salesforce Agentforce, using infrastructure-as-code (Terraform, Bicep, ARM) and CI/CD pipelines.
-- Build and maintain reusable platform components, modules, and landing zones that accelerate AI solution delivery across product teams.
-- Configure and operate core AI platform services (e.g., Azure OpenAI, Azure AI Foundry, AI Search, MuleSoft integration layers, Salesforce Agentforce agents, Antrhopic, OpenAI) in alignment with enterprise architecture standards.
-- Implement environment promotion patterns (dev ------' test ------' prod), secrets management, and observability tooling for AI workloads.
(2) Governance & Guardrails Enablement
-- Translate AI governance policies (risk tiering, model approval, PHI/PII handling, audit logging) into enforceable technical controls: policy-as-code, Azure Policy, RBAC, network isolation, and data egress restrictions.
-- Implement controls that enforce HIPAA, CMS, and internal compliance requirements for AI solutions, including Zero Data Retention configurations, audit log integration, and prompt/response logging where required.
-- Partner with the AI Governance Lead and Coordinator to ensure platform configurations match documented governance posture and are audit-ready.
-- Configure model gateways, content safety filters, bias/PII safeguards, and usage telemetry to support responsible AI operations at scale.
(3) Developer Enablement
-- Deliver paved-path templates, starter kits, and self-service capabilities that allow product and engineering teams to build AI solutions safely without recreating platform components.
-- Provide technical support, documentation, and office hours to development teams consuming the AI platform.
-- Collaborate with Consultant Product Owners and platform architects to translate solution requirements into platform capabilities and backlog items.
(4) Operations & Reliability
-- Monitor platform health, capacity, cost, and consumption; implement automation to optimize spend and performance.
-- Support incident response, root-cause analysis, and continuous improvement of platform reliability and security posture.
-- Maintain platform documentation, runbooks, and architectural decision records.

Required Skills
- Bachelor's degree in Computer Science, Engineering, or related field; equivalent experience considered.
- 5+ years of cloud platform engineering experience, with 2+ years focused on Azure (or comparable hyperscaler).
- Hands-on experience with infrastructure-as-code (Terraform/Bicep), CI/CD pipelines (Azure DevOps, GitHub Actions), and policy-as-code frameworks.
- Working knowledge of AI/ML platform services" Azure OpenAI, AI Foundry, vector databases, model gateways, or equivalent.
- Experience implementing technical controls for regulated data environments (HIPAA, PCI, or similar).
- Strong understanding of identity, networking, encryption, and secrets management patterns in the cloud.

Preferred Qualifications
- Platform familiarity across Azure, MuleSoft, and Salesforce Agentforce " ability to configure, integrate, and govern AI workloads spanning all three platforms.
- Experience operating AI or data platforms in a healthcare payer or other regulated industry.
- Familiarity with AI governance frameworks (NIST AI RMF, ISO 42001) and translating policy into technical enforcement.
- Experience with document intelligence, RAG architectures, or agentic AI patterns.
- Azure certifications (AZ-305, AZ-400, AI-102), MuleSoft Certified Developer/Architect, or Salesforce Agentforce/Platform credentials a plus.